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http://dx.doi.org/10.14400/JDC.2021.19.7.057

The effect of COVID-19 characteristics and transmission risk concerns on smart learning acceptance: Focusing on the application of the integrated model of ISSM and HBM  

Pyo, GyuJin (Keimyung University Management Information Systems)
Kim, Yang Sok (Keimyung University Management Information Systems)
Noh, Mijin (Keimyung University Management Information Systems)
Han, Mu Moung Cho (Dongguk University-Gyeongju PARMITA College)
Rahman, Tazizur (Keimyung University Management Information Systems)
Son, Jaeik (Keimyung University Management Information Systems)
Publication Information
Journal of Digital Convergence / v.19, no.7, 2021 , pp. 57-70 More about this Journal
Abstract
As COVID-19 spreads, people's interest in smart learning that can do non-face-to-face learning is increasing nowadays. In this study, we aim to empirically analyze how users' thoughts on COVID-19 and the information quality and system quality of smart learning systems affect users' acceptance of smart learning and examine the effect of perceived sensitivity and severity of COVID-19 on the satisfaction and use of smart learning through concerns about the risk of transmission. In addition, we examined the influence of information quality composed of content quality and interaction quality and system quality composed of system accessibility and functionality on the use of smart learning through user satisfaction. To verify the validity of the proposed model, we conducted a survey on 334 users with experience in using smart learning, and performed the analysis using Smart PLS 3.0. According to the analysis results, among information quality and system quality, only functionality has a positive (+) effect on the satisfaction of smart learning, and satisfaction has a positive (+) effect on the usage behavior. However, it is found that accessibility among system quality do not affect satisfaction, and concern about the risk of transmission has a negative effect on satisfaction. This study can provide meaningful guidelines to researchers when researching smart learning to support students' learning in a pandemic situation of a new infectious disease, such as COVID-19. It will also be able to provide useful implications for educational institutions and companies related to smart learning.
Keywords
COVID-19; Smart Learning Quality; Transmission Risk Concern; HBM; Usage of Smart learning;
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